Hello! What is the true definition of MA plot? The limma::plotMA displays Expression log-ratio of one sample vs. others even with NGS platform data.

My understanding is this package was developed for microarrays with two-color data and MA plots then were useful to see one sample/array vs. others. I could not find an explanation for how to look at log-ratio for the mean expression of all NGS platform data in an experiment in the limma user's manual.

Thank you!

Lisa

The following article summarizes the history and definition of MA plots:

 http://nar.oxfordjournals.org/content/43/7/e47

See the section on "Mean-difference plots".

Briefly, the concept of an MA plot was created 13-14 years ago by the sma package for a single two colour array, by the rma package for a pair of single channel arrays, and by the limma package for a fitted model or for a matrix of log expression values. These packages provided the original definitions of what an MA plot is.

I'm not quite sure of what you are trying to achieve or why you are having difficulties. To run limma on NGS data you simply run the voom transformation or else use edgeR's cpm function to convert to logCPM. Then you run the analysis similarly as for microarray data.

The definition of an MA plot is a scatter plot with geometric mean intensities on the horizontal axis, and log ratios on the vertical axis. It's essentially a Bland-Altman plot comparing two samples. What two samples you choose to use depends on what you are trying to show. If you are trying to show differences between two samples, then you would want to plot the two samples.

I generally don't use MA plots in that way, instead preferring to use them to look for obvious sample-specific problems, in which case I don't want to look at all pairwise comparisons. Instead, I want to look at each sample versus a single representative sample. Rather than arbitrarily picking one sample, I construct a pseudo sample based on the median value for each gene over all samples, and then do MA plots against that. Something like

 maplot <- function (object){

## this could be better
    if (is(object, "ExpressionSet")) {
        mat <- exprs(object)
    }
    else {
        mat <- as.matrix(object)
    }
    med <- apply(mat, 1, median, na.rm = TRUE)
    M <- mat - med
    A <- (mat + med)/2
    df <- data.frame(M = as.vector(M), A = as.vector(A), Id = colnames(mat)[col(mat)])
    g <- ggplot(df, aes(A, M)) + geom_point(size = 0.05) + facet_wrap(~Id)
    g
}